Wide Range of Recognizable Characters
The system supports multiple recognition engines such as printed Chinese characters, printed English, printed numbers, handwritten Chinese characters, handwritten English, handwritten numbers, magnetic codes, barcodes, customer signature detection, and attachment seal detection.
Good at layout differentiation; accurately classify bills according to such features as inner frame line style, frame line color, title content, title color, text content, and text color
Support such functions as automatic black edge removal, deviation correction, color cast correction, color filtering, noise reduction, binarization, enhanced recognition of unit contract, etc
Supports table recognition with frame lines and table recognition without frame lines. The system automatically detects and recognizes without manual intervention.
Provide Standard API
Support C++, C#, JAVA and other development language calls. Provide standard DLL to integrate with enterpise's ERP, CRM
Output Structural Data
Return JSON, XML recognition result
Multiple Deployment Methods
Support privatized deployment at Windows and Linux servers
Multiple Recognition Methods
Support recognize black and white image and color image
Template classification is accurate
- The recognition rate of template classification is as high as 98%
High Recognition Rate
- The recognition rate of printed Chinese characters is 99.5%. The recognition rate of printed English and numbers is higher than 99.6%
- Black and white bill image: 0.3~0.5s per sheet. Color bill image:0.3~1.0s per sheet
Provide Customization OCR Service
- Quickly response to the development demands of various customized templates
- Bank Supervision System
- Insurance Company
- Evaluation Industry
Bank Supervision System
The form bill recognition system is mainly used in the bank's post-surveillance system to help banks solve the identification and classification of bill images in the risk supervision system. Banks that have been traded include the four major banks of the ICBC, ABC,BCM, CCB ,Jinzhou Bank, Anhui Agricultural Credit, Hainan Bank, and Xinjiang Major banks such as Rural Credit Union.
Staff input paper insurance policies into the insurance imaging system manually is slow,low accurate, and high in labor costs, which slows down the informatization development process of the insurance industry seriously. Our OCR tecnology can integrate with the insurance imaging system to achieve rapid input of insurance policy information so as to improve work efficiency and save labor costs, it has been successfully applied to insurance companies such as Sunshine Insurance, Taiping Insurance, and United Life Insurance.
During various examinations or evaluations, OMR (cursor character recognition) products are used for information collection to identify various evaluation forms and questionnaires. This product has high requirements about printing paper quality and high cost of use. Many manufacturers are seeking lower costs and ensuring accuracy and high speed of the product, Our OCR recognition product helps various examinations and evaluations to input information quickly with high accuracy and low cost.
The recommended: size of the image is about 200KB, and the bit depth is more than 24Recommended resolution of scanned image: 300dpi, less than 3m.
- JSON Data